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The Journal of Supercomputing

Erschienen in:

23.06.2018

Integer linear programming-based cost optimization for scheduling scientific workflows in multi-cloud environments

verfasst von: Somayeh Mohammadi, Hossein Pedram, Latif PourKarimi

Erschienen in: The Journal of Supercomputing | Ausgabe 9/2018

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Abstract

Given that multi-cloud environments contain considerably diverse resources, scheduling workflows in these environments significantly reduces financial costs and overcomes the resource limitations imposed by commercial cloud providers. Accordingly, this study addressed the problem of scientific workflow scheduling in multi-cloud settings under deadline constraint to minimize associated financial costs. To this end, we proposed integer linear programming models that can be solved in a reasonable time by available solvers. In a mathematical model, the objective of a problem and real and physical constraints or restrictions are formulated using exact mathematical functions. Such formulation enabled us to comprehensively understand the system under evaluation, consider secondary preferences and post-optimality analysis and apply useful revisions to inappropriately selected input data. We analyzed the treatment of optimal cost under variations in deadline and workflow size. As part of the post-optimality analysis, sensitivity analysis and deadline revision were implemented. Results indicated that our proposed approach outperforms previously developed methods in terms of financial cost reduction.

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https://aws.amazon.com/ec2.

https://www.rightscale.com/lp/state-of-the-cloud.

CloudHarmony Compute Unit.

http://blog.cloudharmony.com/2010/09/benchmarking-of-ec2s-new-cluster.html.

http://iperf.sourceforge.net/.

https://confluence.pegasus.isi.edu/display/pegasus/WorkflowGenerator.

ILOG CPLEX. http://www.ilog.com/products/cplex.

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Titel: Integer linear programming-based cost optimization for scheduling scientific workflows in multi-cloud environments
verfasst von: Somayeh Mohammadi
Hossein Pedram
Latif PourKarimi
Publikationsdatum: 23.06.2018
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 9/2018
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-018-2465-8

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